#133 Case Western Reserve (7-15)

avg: 1175.77  •  sd: 48.84  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
30 Auburn Loss 5-11 1109.26 Feb 3rd Queen City Tune Up 2018 College Open
64 North Carolina-Charlotte Loss 9-11 1213.3 Feb 3rd Queen City Tune Up 2018 College Open
16 North Carolina-Wilmington** Loss 4-11 1284.51 Ignored Feb 3rd Queen City Tune Up 2018 College Open
91 Penn State Loss 8-10 1111.24 Feb 3rd Queen City Tune Up 2018 College Open
151 George Mason Win 11-4 1716.84 Feb 3rd Queen City Tune Up 2018 College Open
40 Iowa Loss 8-13 1128.65 Feb 17th Easterns Qualifier 2018
12 North Carolina State Loss 6-13 1318.86 Feb 17th Easterns Qualifier 2018
73 Michigan State Loss 9-13 1000.98 Feb 17th Easterns Qualifier 2018
23 Georgia Tech Loss 7-11 1277.07 Feb 17th Easterns Qualifier 2018
78 Georgetown Loss 9-10 1290.07 Feb 17th Easterns Qualifier 2018
149 Davidson Win 13-10 1469 Feb 18th Easterns Qualifier 2018
84 Virginia Loss 6-14 802.14 Feb 18th Easterns Qualifier 2018
224 Georgia Southern Win 14-7 1444.13 Feb 18th Easterns Qualifier 2018
144 Dayton Loss 8-11 787.92 Mar 24th CWRUL Memorial 2018
50 Notre Dame Loss 8-13 1043.12 Mar 24th CWRUL Memorial 2018
203 Rochester Loss 10-11 805.73 Mar 24th CWRUL Memorial 2018
105 Wisconsin-Milwaukee Win 11-10 1442.43 Mar 24th CWRUL Memorial 2018
190 Northern Iowa Win 11-9 1224.99 Mar 25th CWRUL Memorial 2018
240 Tennessee Tech Win 15-4 1389.41 Mar 25th CWRUL Memorial 2018
192 Cedarville Win 12-9 1313.08 Mar 25th CWRUL Memorial 2018
45 Illinois State Loss 7-15 986.15 Mar 31st Huck Finn 2018
74 Washington University Loss 10-13 1090.35 Mar 31st Huck Finn 2018
**Blowout Eligible

FAQ

The uncertainty of the mean is equal to the standard deviation of the set of game ratings, divided by the square root of the number of games. We treated a team’s ranking as a normally distributed random variable, with the USAU ranking as the mean and the uncertainty of the ranking as the standard deviation
  1. Calculate uncertainy for USAU ranking averge
  2. Model ranking as a normal distribution around USAU averge with standard deviation equal to uncertainty
  3. Simulate seasons by drawing a rank for each team from their distribution. Note the teams in the top 16 (club) or top 20 (college)
  4. Sum the fractions for each region for how often each of it's teams appeared in the top 16 (club) or top 20 (college)
  5. Subtract one from each fraction for "autobids"
  6. Award remainings bids to the regions with the highest remaining fraction, subtracting one from the fraction each time a bid is awarded
There is an article on Ulitworld written by Scott Dunham and I that gives a little more context (though it probably was the thing that linked you here)